1. Field of the Invention
The present invention generally relates to optical measurements, and, more specifically, to a method of and apparatus for measuring spatial signal power and spatial noise power of imaging system components by generating and separating the spatial noise and signal components of an image.
2. Description of the Prior Art
An image is herein defined as a specific pattern of light intended for human viewing. Image spatial noise is herein defined as light which was not intended to be in the image, but has been added to the image by the optical or electronic processes utilized to generate a visual display. Thus, the image spatial noise is derived by subtracting the intended image from the delivered image.
Images are presented for human viewing by printers, Cathode Ray Tube (CRT) displays, LCD displays, or may be created by many different other methods. By way of example, charge coupled device (CCD) cameras change scenes into electronic format which "creates" a series of images for transmission to a storage or reproduction device. Another method is to synthesize images within a computer. All these image sources may be electronically combined and the images thereby produced altered by electronic compression, storage and distribution, special coloration, etc. The image which is viewed on the CRT is the summation of all that precedes it. The resolution and image spatial noise ("jaggies", spurious patterning, and luminance irregularities) are limited by each contributor to the electronic images as well as by the display itself--therein lies the problem.
For many imaging systems it is difficult for the display system designer to identify the specific component or subassembly in the display system, e.g., the display head, symbol generator, transmission system, and sensors, that impairs the intended image, and to what degree the intended image was degraded or improved by implementing a design change. Heretofore the subject of image quality was based upon subjective measures, as visually observed by the operator (c.f. L. A. Nelson, R. M. Maner, M. J. Lengyel, M. Seo, Measures of Image Quality, Society for Information Display International Symposium Digest of technical papers, pp 768-771, 1991).
Image quality has historically been a subjective entity measurable only through psychophysical experimentation and statistical analysis of many observers' opinions. The psychophysical measures are extremely complex because chromatic, temporal, and luminance errors all contribute to perception of image quality. As these contributions are not readily measured in practice, comparisons between overall image quality determinations has heretofore not been feasible.
As a measure of image noise, image compression algorithms frequently refer to the total squared error between compressed and uncompressed images, where the error is determined by the difference between the input image and the reconstructed image following decompression. The problem with this method is that it is a metric which does not lend itself to a general characterization. The answer depends on the complexity of the input image. Further, the spatial distribution of noise energy such as spurious patterning is not described quantitatively by the squared error measurement, so that the measure cannot be correlated to perceived image quality.
The particular distribution of errors in an image profoundly affects the subjective impact of those errors. An example of this sensitivity is the impairment caused by addition of color subcarriers (NTSC, SECAM, PAL). By carefully planning and controlling the subcarrier frequencies relative to the scanning frequencies, the patterned noise subjectively observed is minimized. The magnitude of subcarrier is not the sensitive issue here. For a particular magnitude of subcarrier, the patterns it produces can be changed to be less subjectively impairing by the relative choice of frequencies.
Noise caused by external sources (such as switching power supplies) also causes image impairment. For equal energy, the patterned noise energy sources are much more impairing than noise energy sources which do not create spurious patterns in an image.
An apparatus and method of use is needed to characterize the spatial noise properties and spatial signal properties of an imaging system in a general sense, similar to noise measurements associated with time varying signals, where a particular input signal is applied and the resulting output is recorded and analyzed. By way of example, an audio engineer may use sine waves of selected frequencies and amplitudes to stimulate his audio system and measure the signal-to-noise power ratio using a spectrum analyzer. Similarly, a video engineer needs an instrument to measure the signal-to-noise power ratio of his video system component, so that a meaningful analytical measurement will guide changes within the video system and establish the level of performance based upon an objective measure of the imaging capability of the system. Here, we refer not to electronic noise power but to the spatial noise in the resulting output image.
While components in imaging systems are judged by the quality of a delivered image, no method or apparatus exists which accurately measures the spatial noise properties associated with a high quality image. The present invention defines one such property as the spatial signal to spatial signal-plus-noise power ratio. The present invention creates spatial frequency power spectrum representations by optical means from specially selected image primitives. The spatial image to power spectral density conversion is accomplished via an optical, two-dimensional Fourier transform of the input image. Using this transformation, the signal power and noise power are separable through spatial filtering. Measurements of these power terms enable signal/signal-plus-noise power ratio calculations which serve as an objective measure of spatial noise.
It is known that an image may be spatially filtered by performing an optical Fourier transformation of the input image and applying a spatial filter or mask at the Fourier image plane selectively to remove spatial frequency components. See, for example, J. W. Goodman, Introduction to Fourier Optics, McGraw-Hill, 1968, pp. 141-149. In U.S. Pat. No. 5,072,314, T. Y. Chang teaches selective amplification of spatial frequency components to provide enhancement of the features of an optically encoded image. The Fourier transform of the input image is a light distribution pattern in which the light intensity varies in accordance with the amplitudes of the spatial frequency components in the input signal, analogous to the Fourier transform of a complex electrical waveform into a plurality of sine waves, but in two dimensions. However, Chang does not measure the power of the spatial frequency components but, rather, reconstructs the image after amplifying selected spectral components, thereby enhancing the image.
In E. F. Brown, et al, U.S. Pat. No. 3,657,550, there is disclosed an apparatus for measuring the spatial response of optical systems (e.g., a television system). A display is generated in a cathode ray tube by means for varying the periodicity of a predetermined spatial waveform image. The optical system under test is disposed between the cathode ray tube and a masked aperture, with a photo-detector disposed behind the mask so as to provide an output proportional to the light intensity as the spatial waveform is slowly scanned with respect to the aperture. Brown et al does not teach the use of an optical Fourier transform to resolve the spatial components of the image as in the present invention, and his stimulus is different than is used for this measurement.
For the foregoing reasons, a need remains in the art for an apparatus and method of objectively determining the signal-to-noise ratio of imaging systems that provides a direct, quantitative measurement of the spatial noise quality of a displayed image and that is essentially independent of subjective influences.